2 months ago
Remote, WorldwideSenior / Staff+
Base Salary
$170k - $260k/yr
Responsibilities
- Design, build, and operate core systems that enable autonomous agents to function reliably in production.
- Build agent execution systems with autonomous task loops, scheduling, triggers, and control planes.
- Develop retrieval, context-management, long-term-memory, and structured-memory architectures.
- Build multi-model routing and orchestration across providers while balancing quality, latency, cost, and failure modes.
- Create safe tool-calling and integration frameworks for external services and enterprise environments.
- Develop reliability, security, observability, evaluation, failure-isolation, and recovery foundations.
- Build enterprise interfaces and governance surfaces for deploying, managing, monitoring, and controlling AI usage.
- Shape product requirements, architectural direction, durable platform defaults, abstractions, and guardrails.
- Measure adoption and impact, iterate on real usage, and improve the product directly.
Requirements
- Experience building and operating complex backend or distributed systems in production.
- Experience building LLM-powered or AI-native systems beyond demos, with real users and real constraints.
- Strong judgment around reliability, security, observability, and failure modes.
- Ability to work in ambiguous frontier areas and validate ideas through rapid iteration.
- High ownership, autonomy, and end-to-end systems responsibility.
- TypeScript proficiency is required.
- Python is strongly preferred.
- Strong SQL proficiency is required.
- Production infrastructure experience is required; Docker and Kubernetes experience is a plus.
- Familiarity with enterprise security patterns is a plus.
- Domain familiarity with DevOps, SecOps, or infrastructure automation is a plus.
- Comfort using AI throughout design, implementation, testing, debugging, and incident response.
Benefits
- Small, highly technical team with high autonomy and ownership.
- Opportunity to work on frontier agentic systems and influence product and architectural direction.
- The role may be deployed on-premises, in hybrid environments, or in the cloud.
- Level, scope, and compensation are calibrated to experience and interview performance.